ABSTRACT
The COVID-19 pandemic makes it difficult for people to carry out their activities, especially those who work in the informal sector. The lower middle class has experienced obstacles in carrying out work and lost income. Social media is one of the media that mediates solidarity movements between communities in each region in Indonesia. This study aims to explain how Twitter mediates the social solidarity movement amid the COVID-19 pandemic in Indonesia. This research is conducted through Twitter analytics processed using machine learning. The authors collected data between March 1 - December 1 of 2020 and analyzed them using machine learning, including polarity sentiment, emotion sentiment, topic in the word cloud, and social network analysis. The findings show that conversations on Twitter concerning solidarity are not just regular conversations. Mediated solidarity conversations on Twitter can influence another solidarity movement within the same hashtag or word cloud topic that reflects society emotions in supporting each other. A positive sentiment regarding these conversations is also relevant with the SNA, showing no contradictions. All these conversations inspired each other to be strong and unify. These public conversations on Twitter indicate the Indonesian community resilience in facing emergency conditions. © 2021 IEEE.